Spot Urine Protein Measurements
Bibliographic record
Abstract
BACKGROUND: Proteinuria and albuminuria are important markers of allograft pathology and are associated with graft loss and cardiovascular disease. Traditionally, these have been quantified using a 24-hr urine collection, but spot urine measurements (albumin-creatinine and protein-creatinine ratios) have become popular because of convenience. Aside from tests of correlation, there has been little evaluation of these measurements in kidney transplantation. METHODS: To further assess the value of albumin-creatinine and protein-creatinine ratios, we measured protein-creatinine ratio and 24-hr urine protein excretion (n=192) and albumin-creatinine ratio and 24-hr urine albumin excretion (n=189) in stable renal transplant patients. Bias (measured minus estimated value), precision, and accuracy was calculated. RESULTS: For the protein-creatinine ratio, percent bias ranged from 12% to 21%, and the accuracy (within 30% of 24-hr collection) was only 47% to 56% depending on the degree of proteinuria. For the albumin-creatinine ratio, percent bias ranged from 9% to 21%, and the accuracy (within 30%) ranged from 38% to 80% depending on the degree of albuminuria. There was no statistical difference between accuracy of protein-creatinine and albumin-creatinine ratios. CONCLUSIONS: The ability of the albumin-creatinine and protein-creatinine ratios to accurately predict 24-hr albumin and protein excretion is modest. Given the similar accuracy of both measurements, either protein-creatinine ratio or albumin-creatinine ratio can be used for monitoring protein excretion. However, given the limitations of both the albumin-creatinine ratio and protein-creatinine ratio in this population, a 24-hr urine collection should be considered before making major clinical decisions (e.g., biopsy) based on the presence of proteinuria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".